Gym Member Lifetime Value (LTV) Calculator

How this calculator works

This is a screening tool for the unit economics of a gym, boutique studio, or wellness facility from a single member's perspective. The core anchor is the standard SaaS-style lifetime-value formula adapted for monthly subscription fitness:

LTV per member = ARPU times gross margin times (1 divided by monthly churn).

The factor of one divided by monthly churn is the perpetuity expression for the expected member tenure in months under the assumption that churn is constant over time. A 5% monthly churn implies an expected tenure of 1 divided by 0.05, or 20 months. Multiplying by ARPU produces the recurring revenue the member is expected to deliver over that tenure; multiplying again by gross margin produces the contribution margin — the dollar amount available, after variable cost of service, to cover acquisition, fixed costs, and operator return.

The output is a unit-economics screen, not a forecast. It tells the operator whether each marginal new member is contribution-positive, how quickly the acquisition spend pays back, and whether the LTV-to-CAC ratio sits in a healthy band against the industry benchmarks. It does NOT model cohort-specific churn curves, annual-plan discount effects, ancillary revenue, seasonality, or pricing-tier mix — operators who need any of those should layer a cohort analysis or commission a credentialed CFO to build a finite-horizon model on top of this baseline.

The calculator reports LTV per member as the headline number, total gross LTV across the active member base, expected tenure in months, monthly contribution per member, CAC payback in months, the LTV-to-CAC ratio with a health flag (STRONG, HEALTHY, WARNING, UNHEALTHY), current MRR, projected MRR in 12 months under compounding net member growth, and projected ARR at the 12-month point.

ARPU vs gross billing — what to include

ARPU in this calculator is the monthly RECURRING revenue per active member: base dues, locker fees, towel-service add-ons, app access, and any embedded recurring small-group or wellness subscriptions. Non-recurring revenue — personal-training packages, retail, day passes, F&B, supplement sales — should NOT go into ARPU directly.

The cleanest approach for ancillary revenue is to use the gross-margin lever to capture it. If trailing-twelve-month PT contribution adds $20 of monthly margin per active member, the operator can model recurring ARPU at the dues figure and lift the gross-margin assumption by enough to incorporate the PT contribution. The alternative is to compute a blended ARPU that amortizes ancillary across the active base — defensible but mixes high-volatility revenue into the LTV calculation, which produces unstable period-over-period numbers.

The cleanest financial model treats recurring and ancillary as two distinct revenue streams with their own margins and applies the perpetuity LTV only to the recurring stream. Ancillary revenue is then modeled separately as a contribution overlay, with its own volatility and its own marketing economics. Operators in the boutique format where premium PT or retail materially dominates the P&L should be especially careful to separate the streams — running everything through a single blended ARPU obscures both the recurring economics and the ancillary economics.

Benchmark ARPU ranges from the IHRSA Industry Data Survey and ClubIntel operator reports: big-box gyms cluster at $40-60 monthly; mid-market full-service clubs at $80-120; boutique studios (cycling, F45, reformer Pilates) at $150-250 effective monthly via class packs amortized into recurring billing; functional fitness (CrossFit, F45) at $130-200; high-end wellness clubs (Equinox, Life Time premium tier) at $200-300.

Monthly churn — the perpetuity assumption and its real-world break-point

The perpetuity formula treats monthly churn as constant and memoryless. A facility with 5% monthly churn loses 5% of its active members every month forever, and any single member faces a 5% probability of cancellation in any given month regardless of how long they have been a member. Under that assumption, the expected tenure is exactly one divided by the monthly churn rate — a mathematical identity for exponential decay.

The real-world break-point is well documented in IHRSA retention research and in Brian Balfour's Reforge work: fitness churn is heavily FRONT-LOADED. The first 90 days see 25-40% of new members lapse, driven by New Year resolution fatigue, free-trial-to-paid conversion failures, schedule mismatches, and onboarding gaps. Members who survive past day 90 exhibit monthly churn rates 50-70% lower than the overall facility average. The constant-churn perpetuity formula therefore OVERSTATES LTV relative to a cohort-survival model — typically by 10-25%, depending on how steep the early-dropout cliff is.

The practical implication is that the calculator output is a planning baseline, not a precise number. Operators with strong onboarding programs and milestone check-ins at day 30, day 60, and day 90 will outperform the perpetuity estimate; operators with weak onboarding will underperform it. The IHRSA Industry Data Survey ten-year average for monthly churn is 4-7% across formats, with big-box gyms at 3-5%, boutique studios at 5-9%, and functional fitness at 4-6%. Operators benchmarking outside their format range should investigate the cohort curve before trusting the headline LTV.

For operators who need a defensible number for facility valuation, debt-service coverage, or earn-out negotiation, the perpetuity formula is insufficient. Commission a cohort-survival analysis from your member-management system data, fit a Kaplan-Meier curve to the actual tenure distribution, and integrate the curve numerically — the resulting LTV will be lower than the perpetuity number but more defensible in any external diligence context.

Customer Acquisition Cost — what counts

Fully-loaded CAC includes everything spent to acquire a net new member. The components:

• Paid advertising spend. Meta, Google, TikTok, programmatic display, out-of-home, local radio, direct mail. Include creative-production and agency-management fees as part of the spend, not separately.
• Referral incentives. Cash referral bonuses paid to existing members, free-month credits redeemed, equipment giveaways tied to referrals.
• Free-trial costs. The dues, locker, and towel-service value forgiven during free trials, plus any direct giveaways (water bottles, branded swag) handed out during the trial.
• Agency and creative fees. Performance marketing agency retainers, video and photo production costs, copywriting fees.
• Staff compensation allocation. The fraction of front-desk and sales-team compensation attributable to acquisition activity — typically the proportion of staff hours spent on tours, trial conversions, and follow-up calls. A common heuristic is 30-50% of front-desk comp for high-acquisition facilities, 10-20% for low-acquisition or membership-stable facilities.

To compute CAC, divide TOTAL acquisition spend in a period by NET new members in the same period — gross new members minus the members who churned in that period. A common error is to use gross new members, which understates CAC by ignoring the running cost of replacing the steady-state churn base.

What does NOT count as CAC: retention investment (post-join onboarding, member events, loyalty programs), facility costs (rent, equipment, base salaries, utilities), capital investment (new equipment, renovations), or community-engagement spend that is not directly tied to new-member acquisition. The cleanest internal definition is "all spend that would zero out if the operator paused all new-member acquisition for one period."

Benchmark CAC ranges: big-box gyms with strong digital funnels run $100-200 per net new member; boutique studios where free-trial conversion dominates run $250-500; functional-fitness facilities with strong word-of-mouth run $50-150; high-end wellness clubs with concierge sales teams run $500-1,500.

LTV-to-CAC ratio — interpretation bands

The LTV-to-CAC ratio is the dollar of contribution margin returned per dollar of acquisition spend, over the expected member tenure. The calculator surfaces a health flag based on the canonical SaaS interpretation bands (David Skok, Bessemer State of the Cloud, OpenView Partners), which translate cleanly to the fitness-operator context:

• STRONG (5.0-to-1 or higher). Unit economics are excellent and the operator is likely UNDER-INVESTING in acquisition. The defensible action is to lean in on marketing spend — the ratio has room to compress to 3.0-to-1 before the unit economics turn warning, and the incremental members will drive growth that fixed-cost leverage cannot match. Many strong-ratio facilities are leaving meaningful growth on the table by being too conservative on the marketing budget.
• HEALTHY (3.0-to-1 to 5.0-to-1). Unit economics are sustainable and the operator has appropriate margin of safety. Continue current acquisition strategy; consider modest spend increases if there is operational capacity for the resulting member volume. This is the target band for steady-state operations.
• WARNING (1.0-to-1 to 3.0-to-1). Unit economics are positive but barely. There is no margin of safety against a churn spike, a CAC creep, or a competitive pricing move. The defensible action is to investigate ALL FOUR levers: ARPU (can prices rise, can ancillary attach increase), gross margin (can variable cost of service come down), churn (can onboarding reduce day-90 dropouts), and CAC (which channels are inefficient). Do NOT lean in on additional marketing spend at this ratio — the incremental members will compress the ratio further toward the unsustainable zone.
• UNHEALTHY (below 1.0-to-1). The facility loses contribution margin on each new member. This is unsustainable; the operator must either drop CAC, raise ARPU, reduce churn, or improve gross margin before continuing to acquire. Continuing to spend on acquisition at sub-1-to-1 economics is destroying value.

The thresholds are HEURISTICS, not laws. A facility with strong forward visibility (long contracts, low cohort variance, high net-dollar retention from ancillary upsell) can defend a lower ratio; a facility with high cohort variance or seasonal demand should defend a higher one.

Industry benchmarks (IHRSA)

The IHRSA Industry Data Survey is the most-cited operator-benchmarking dataset in the global health-club industry. The ten-year averages most relevant to the unit-economics screening:

• Monthly attrition across formats runs 4-7%. Big-box gyms run 3-5% (lower price means lower perceived loss when cancelling); boutique studios 5-9% (higher engagement but higher price sensitivity); functional fitness 4-6% with strong tribal retention; high-end wellness clubs 3-5% with concierge retention programs.
• ARPU clusters as covered above: $40-60 big-box, $80-120 mid-market, $150-250 boutique, $130-200 functional fitness, $200-300 high-end wellness.
• Gross margin runs 70-85% across most formats once rent and equipment are sunk. Boutique studios with per-class instructor pay trend lower (60-75%); unstaffed 24-hour gyms trend higher (80-90%).
• CAC payback benchmarks: under 12 months is the strong signal for big-box; 12-18 months is acceptable for premium boutique where high ARPU offsets higher acquisition cost; over 18 months is a red flag in every format.
• LTV-to-CAC ratio benchmarks track the canonical SaaS bands: above 3-to-1 healthy, above 5-to-1 under-investing in acquisition, below 1-to-1 unit-negative. Mature facilities in the steady-state ratio band of 3-to-1 to 5-to-1 are the modal case.

ClubIntel operator reports add further segmentation by region, age of facility, and ownership structure (independent vs franchise vs corporate). The benchmarks are not normative — they describe the population, not what any specific facility SHOULD do — but they are the most defensible external anchor available for operator-side planning.

What this calculator does NOT model

Five exclusions, in descending order of importance:

Cohort-specific churn curves. The perpetuity formula treats churn as a single constant rate. Real fitness churn is front-loaded, with 25-40% of new members lapsing in the first 90 days and the survivors exhibiting much lower steady-state churn. The constant-churn LTV typically overstates the cohort-curve LTV by 10-25%. For any consequential decision (facility valuation, debt service, earn-out), commission a cohort-survival analysis.

Annual-plan discount effects. Members on prepaid annual contracts have effectively zero monthly churn but a different effective ARPU. Treat them as a separate cohort; running blended numbers obscures both segments. Annual-plan acquisition also tends to have different CAC dynamics — typically higher upfront acquisition cost with materially better retention.

Ancillary revenue per member. Personal training, retail, F&B, and corporate-wellness contracts contribute material margin at most facilities. The cleanest approach is to model recurring and ancillary as separate revenue streams with their own margins. Loading ancillary into the recurring ARPU produces unstable period-over-period numbers because ancillary attach rates fluctuate.

Seasonality. The January acquisition spike and summer trough are real and material — January acquisition volume is often 2-3 times the monthly average; summer is often 0.5-0.7 of the average. The calculator's steady-state assumption is appropriate for annual planning but produces misleading numbers for any single month.

Pricing-tier mix and complex membership structures. A facility with a $39 basic tier and a $129 premium tier should run the calculator separately per tier and weight the results. Family memberships, corporate-wellness contracts, and prepaid multi-month packages each have distinct unit economics; a blended single-tier model obscures the segment-level signals.

Operators who need any of these layers should commission a cohort analysis from a credentialed CFO or financial planner who can build a finite-horizon DCF and a tier-weighted cohort model on top of this baseline.

Sources

The methodology and benchmarks in this calculator draw on the following sources:

• IHRSA — Industry Data Survey. The standard global benchmark dataset for health-club operators; ten-year monthly-attrition data, ARPU segmentation by facility model, and the source of the 4-7% monthly churn baseline. ihrsa.org/publications
• IHRSA — Retention research library. Operator-facing material on the front-loaded shape of fitness churn (90-day, 180-day, 12-month cohort survival) and the interventions that move the survival curve. ihrsa.org/improve-your-club/industry-news/retention
• ClubIntel — Fitness Industry Operator Reports. Operator-side benchmarking research covering ARPU, retention curves, ancillary-revenue contribution, and member-experience metrics across formats. club-intel.com/research
• David Skok — SaaS Metrics 2.0 (For Entrepreneurs). The canonical derivation of the LTV equation (ARPU times gross margin divided by churn) and the 3-to-1 LTV-to-CAC rule of thumb. forentrepreneurs.com/saas-metrics-2
• OpenView Partners — SaaS Benchmarks Report. Annual benchmarks covering LTV-to-CAC, CAC payback, net-dollar-retention, and gross-margin distributions across the subscription business landscape. openviewpartners.com
• Bessemer Venture Partners — State of the Cloud Report. Published interpretation bands for LTV-to-CAC (above 3-to-1 healthy, above 5-to-1 under-investing in growth). bvp.com/atlas
• Brian Balfour — Reforge: Four Fits Framework. The framework that clarifies why the constant-churn perpetuity formula overstates LTV when actual churn is front-loaded. brianbalfour.com/four-fits-growth-framework
• Tomasz Tunguz — Redpoint unit economics writings. The multiplicative interaction between gross margin, ARPU, and churn in setting the maximum-defensible CAC. tomtunguz.com

Last reviewed: 2026-05-16 against the IHRSA Industry Data Survey ten-year averages, ClubIntel operator benchmark reports, David Skok's SaaS Metrics 2.0 derivation of the LTV equation, the OpenView Partners SaaS Benchmarks Report, the Bessemer State of the Cloud LTV-to-CAC interpretation bands, and Brian Balfour's Reforge framework for cohort-curve corrections to the perpetuity LTV formula. The constant-churn perpetuity formula remains the industry-standard planning approximation; cohort-survival analysis is the appropriate refinement for valuation, lending, or earn-out contexts.